From leaf to multiscale models of photosynthesis: applications and challenges for crop improvement.

Autor: Stirbet A; Newport News, USA., Guo Y; Key Laboratory of Advanced Process Control for Light Industry, Ministry of Education Jiangnan University, Wuxi, 214122, China., Lazár D; Department of Biophysics, Faculty of Science, Palacký Univesity, Šlechtitelů 27, 78371, Olomouc, Czech Republic., Govindjee G; Department of Biochemistry, Department of Plant Biology, and the Center of Biophysics & Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, USA. gov@illinois.edu.
Jazyk: angličtina
Zdroj: Photosynthesis research [Photosynth Res] 2024 Aug; Vol. 161 (1-2), pp. 21-49. Date of Electronic Publication: 2024 Apr 15.
DOI: 10.1007/s11120-024-01083-9
Abstrakt: To keep up with the growth of human population and to circumvent deleterious effects of global climate change, it is essential to enhance crop yield to achieve higher production. Here we review mathematical models of oxygenic photosynthesis that are extensively used, and discuss in depth a subset that accounts for diverse approaches providing solutions to our objective. These include models (1) to study different ways to enhance photosynthesis, such as fine-tuning antenna size, photoprotection and electron transport; (2) to bioengineer carbon metabolism; and (3) to evaluate the interactions between the process of photosynthesis and the seasonal crop dynamics, or those that have included statistical whole-genome prediction methods to quantify the impact of photosynthesis traits on the improvement of crop yield. We conclude by emphasizing that the results obtained in these studies clearly demonstrate that mathematical modelling is a key tool to examine different approaches to improve photosynthesis for better productivity, while effective multiscale crop models, especially those that also include remote sensing data, are indispensable to verify different strategies to obtain maximized crop yields.
(© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)
Databáze: MEDLINE
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